Integrative analysis of miRNA-mRNA network in high altitude retinopathy by bioinformatics analysis

High-altitude retinopathy (HAR) is an ocular manifestation of acute oxygen deficiency at high altitudes. Although the pathophysiology of HAR has been revealed by many studies in recent years, the molecular mechanism is not yet clear. Our study aimed to systematically identify the genes and miRNA and explore the potential biomarkers associated with HAR by integrated bioinformatics analysis. The mRNA and miRNA expression profiles were obtained from the GEO database. We performed Gene Ontology (GO) functional annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Potential target gene analysis and miRNA-mRNA network analysis were also conducted. Quantitative RT-PCR (qRT-PCR) was used to validate the results of the bioinformatics analysis. Through a series of bioinformatics analyses and experiments, we selected 16 differentially expressed miRNAs (DE-miRNAs) and 157 differentially expressed genes (DEGs) related to AMS and constructed a miRNA-mRNA network containing 240 relationship pairs. The hub genes were filtered from the PPI network: IL7R, FOS, IL10, FCGR2A, DDX3X, CDK1, BCL11B and HNRNPH1, which were all downregulated in the AMS group. Then, 9 upregulated DE-miRNAs and 8 hub genes were verified by qRT-PCR in our hypoxia-induced HAR cell model. The expression of miR-3177-3p, miR-369-3p, miR-603, miR-495, miR-4791, miR-424-5p, FOS, IL10 and IL7R was consistent with our bioinformatics results. In conclusion, FOS, IL10, IL-7R and 7 DE-miRNAs may participate in the development of HAR. Our findings will contribute to the identification of biomarkers and promote the effective prevention and treatment of HAR in the future.

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Identification of lncRNA–mRNA Regulatory Network Associated With Isolated Systolic Hypertension and Atherosclerotic Cerebral Infarction

10.21203/rs.3.rs-391143/v1 ◽

2021 ◽

Author(s):

jie Yang ◽

Yan-Nan Tao ◽

Fang-Xiao Hu ◽

Yong-Zhi Chen ◽

Xue-Song Yang ◽

...

Keyword(s):

Cerebral Infarction ◽

Regulatory Network ◽

Systolic Hypertension ◽

Expression Profiles ◽

Pearson Correlation ◽

Interaction Network ◽

Differentially Expressed ◽

Isolated Systolic Hypertension ◽

Hub Genes ◽

Qrt Pcr

Abstract Background: Increasing evidences uncover that lncRNAs play an important role in Isolated systolic hypertension (ISH). However, a systematic lncRNA-mRNA regulatory network is still absent in isolated systolic hypertension and atherosclerotic cerebral infarction patients (ISH & ACI).Aim:This research aims to establish a lncRNA-mRNA co-expression network in patients with ISH & ACI, to probe into the potential functions of lncRNA in those patients.Design and Setting:Expression profiles of lncRNA and mRNAs are collected and compared respectively from 8 patients with ISH and 8 patients with ISH & ACI by RNA-seq data.Methods: Differentially expressed lncRNAs and mRNAs were screened out via high-throughput sequencing in the plasma of ISH/ACI patients and control ISH patients. Then, a lncRNA-mRNA interaction network was built using the Pearson correlation coefficient by Cytoscape software. The expression levels of the hub genes and lncRNAs were verified by qRT-PCR in another 10 ISH/ACI patients and 10 control patients. Results: 2768 differentially expressed lncRNAs and 747 differentially expressed mRNAs were identified. 2 hub genes (CD226 and PARVB) and 11 lncRNAs were identified in the lncRNA-mRNA interaction network. qRT-PCR and cell assay results verified that lncRNAs ENST00000590604 and CD226 are highly expressed in patients of ISH & ACI. CD226 was associated with vascular endothelial cells growth and stability through platelet activation and focal adhesion pathway.Conclusion: We established a novel mRNA-lncRNA interaction network. lncRNAs ENST00000590604 and CD226 might be the potential biomarkers of ISH & ACI.

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Differential Expression Profiles of Long Noncoding RNA and mRNA of Osteogenically Differentiated Mesenchymal Stem Cells in Ankylosing Spondylitis

The Journal of Rheumatology ◽

10.3899/jrheum.151181 ◽

2016 ◽

Vol 43 (8) ◽

pp. 1523-1531 ◽

Cited By ~ 24

Author(s):

Zhongyu Xie ◽

Jinteng Li ◽

Peng Wang ◽

Yuxi Li ◽

Xiaohua Wu ◽

...

Keyword(s):

Stem Cells ◽

Mesenchymal Stem Cells ◽

Ankylosing Spondylitis ◽

Osteogenic Differentiation ◽

Noncoding Rna ◽

Bioinformatics Analysis ◽

Expression Profiles ◽

Differentially Expressed ◽

Qrt Pcr ◽

Pcr Assays

Objective.We previously demonstrated that mesenchymal stem cells (MSC) from patients with ankylosing spondylitis (AS; ASMSC) have a greater osteogenic differentiation capacity than MSC from healthy donors (HDMSC) and that this difference underlies the pathogenesis of pathological osteogenesis in AS. Here we compared expression levels of long noncoding RNA (lncRNA) and mRNA between osteogenically differentiated ASMSC and HDMSC and explored the precise mechanism underlying abnormal osteogenic differentiation in ASMSC.Methods.HDMSC and ASMSC were induced with osteogenic differentiation medium for 10 days. Microarray analyses were then performed to identify lncRNA and mRNA differentially expressed between HDMSC and ASMSC, which were then subjected to bioinformatics analysis and confirmed by quantitative real-time PCR (qRT-PCR) assays. In addition, coding-non-coding gene co-expression (CNC) networks were constructed to examine the relationships between the lncRNA and mRNA expression patterns.Results.A total of 520 lncRNA and 665 mRNA were differentially expressed in osteogenically differentiated ASMSC compared with HDMSC. Bioinformatics analysis revealed 64 signaling pathways with significant differences, including transforming growth factor-β signaling. qRT-PCR assays confirmed the reliability of the microarray data. The CNC network indicated that 4 differentially expressed lncRNA, including lnc-ZNF354A-1, lnc-LIN54-1, lnc-FRG2C-3, and lnc-USP50-2 may be involved in the abnormal osteogenic differentiation of ASMSC.Conclusion.Our study characterized the differential lncRNA and mRNA expression profiles of osteogenically differentiated ASMSC and identified 4 lncRNA that may participate in the abnormal osteogenic differentiation of ASMSC. These results provide insight into the pathogenesis of pathological osteogenesis in AS.

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An integrative bioinformatics analysis of microarray data for identifying hub genes as diagnostic biomarkers of preeclampsia

Bioscience Reports ◽

10.1042/bsr20190187 ◽

2019 ◽

Vol 39 (9) ◽

Cited By ~ 2

Author(s):

Keling Liu ◽

Qingmei Fu ◽

Yao Liu ◽

Chenhong Wang

Keyword(s):

Gene Expression ◽

Microarray Data ◽

Bioinformatics Analysis ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Support Vector ◽

Hub Genes ◽

Diagnostic Biomarkers

Abstract Preeclampsia (PE) is a disorder of pregnancy that is characterised by hypertension and a significant amount of proteinuria beginning after 20 weeks of pregnancy. It is closely associated with high maternal morbidity, mortality, maternal organ dysfunction or foetal growth restriction. Therefore, it is necessary to identify early and novel diagnostic biomarkers of PE. In the present study, we performed a multi-step integrative bioinformatics analysis of microarray data for identifying hub genes as diagnostic biomarkers of PE. With the help of gene expression profiles of the Gene Expression Omnibus (GEO) dataset GSE60438, a total of 268 dysregulated genes were identified including 131 up- and 137 down-regulated differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs suggested that DEGs were significantly enriched in disease-related biological processes (BPs) such as hormone activity, immune response, steroid hormone biosynthesis, metabolic pathways, and other signalling pathways. Using the STRING database, we established a protein–protein interaction (PPI) network based on the above DEGs. Module analysis and identification of hub genes were performed to screen a total of 17 significant hub genes. The support vector machines (SVMs) model was used to predict the potential application of biomarkers in PE diagnosis with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.958 in the training set and 0.834 in the test set, suggesting that this risk classifier has good discrimination between PE patients and control samples. Our results demonstrated that these 17 differentially expressed hub genes can be used as potential biomarkers for diagnosis of PE.

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Identification of lncRNA–mRNA Regulatory Network Associated With Isolated Systolic Hypertension And Atherosclerotic Cerebral Infarction

10.21203/rs.3.rs-391143/v2 ◽

2021 ◽

Author(s):

Jie Yang ◽

Yan-Nan Tao ◽

Fang-Xiao Hu ◽

Yong-Zhi Chen ◽

Xue-Song Yang ◽

...

Keyword(s):

Cerebral Infarction ◽

Regulatory Network ◽

Systolic Hypertension ◽

Expression Profiles ◽

Pearson Correlation ◽

Interaction Network ◽

Differentially Expressed ◽

Isolated Systolic Hypertension ◽

Hub Genes ◽

Qrt Pcr

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Comprehensive analysis of an lncRNA-miRNA-mRNA competing endogenous RNA network in pulpitis

PeerJ ◽

10.7717/peerj.7135 ◽

2019 ◽

Vol 7 ◽

pp. e7135 ◽

Cited By ~ 5

Author(s):

Fangcao Lei ◽

Han Zhang ◽

Xiaoli Xie

Keyword(s):

Differentially Expressed Genes ◽

Protein Interaction ◽

Dental Pulp ◽

Expression Profiles ◽

Differentially Expressed ◽

Hub Genes ◽

Regulatory Relationship ◽

Protein Protein Interaction ◽

Qrt Pcr ◽

Ppi Networks

Background Pulpitis is a common inflammatory disease that affects dental pulp. It is important to understand the molecular signals of inflammation and repair associated with this process. Increasing evidence has revealed that long noncoding RNAs (lncRNAs), via competitively sponging microRNAs (miRNAs), can act as competing endogenous RNAs (ceRNAs) to regulate inflammation and reparative responses. The aim of this study was to elucidate the potential roles of lncRNA, miRNA and messenger RNA (mRNA) ceRNA networks in pulpitis tissues compared to normal control tissues. Methods The oligo and limma packages were used to identify differentially expressed lncRNAs and mRNAs (DElncRNAs and DEmRNAs, respectively) based on expression profiles in two datasets, GSE92681 and GSE77459, from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were further analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein–protein interaction (PPI) networks and modules were established to screen hub genes using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the Molecular Complex Detection (MCODE) plugin for Cytoscape, respectively. Furthermore, an lncRNA-miRNA-mRNA-hub genes regulatory network was constructed to investigate mechanisms related to the progression and prognosis of pulpitis. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was applied to verify critical lncRNAs that may significantly affect the pathogenesis in inflamed and normal human dental pulp. Results A total of 644 upregulated and 264 downregulated differentially expressed genes (DEGs) in pulpitis samples were identified from the GSE77459 dataset, while 8 up- and 19 downregulated probes associated with lncRNA were identified from the GSE92681 dataset. Protein–protein interaction (PPI) based on STRING analysis revealed a network of DEGs containing 4,929 edges and 623 nodes. Upon combined analysis of the constructed PPI network and the MCODE results, 10 hub genes, including IL6, IL8, PTPRC, IL1B, TLR2, ITGAM, CCL2, PIK3CG, ICAM1, and PIK3CD, were detected in the network. Next, a ceRNA regulatory relationship consisting of one lncRNA (PVT1), one miRNA (hsa-miR-455-5p) and two mRNAs (SOCS3 and PLXNC1) was established. Then, we constructed the network in which the regulatory relationship between ceRNA and hub genes was summarized. Finally, our qRT-PCR results confirmed significantly higher levels of PVT1 transcript in inflamed pulp than in normal pulp tissues (p = 0.03). Conclusion Our study identified a novel lncRNA-mediated ceRNA regulatory mechanisms in the pathogenesis of pulpitis.

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Comprehensive analysis of circRNA expression profiles and circRNA-associated competing endogenous RNA networks in IgA nephropathy

PeerJ ◽

10.7717/peerj.10395 ◽

2020 ◽

Vol 8 ◽

pp. e10395

Author(s):

Haiyang Liu ◽

Di Liu ◽

Yexin Liu ◽

Ming Xia ◽

Yan Li ◽

...

Keyword(s):

Expression Profiles ◽

Nitrogen Compound ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Competing Endogenous Rna ◽

Hub Genes ◽

Qrt Pcr ◽

Cerna Network ◽

Ppi Networks ◽

Micro Rnas

Background Immunoglobulin A nephropathy (IgAN) is immune-mediated primary glomerulonephritis, which is the most common reason leading to renal failure worldwide. The exact pathogenesis of IgAN is not well defined. Accumulating evidence indicates that circular RNAs (circRNAs) play crucial roles in the immune disease by involving in the competing endogenous RNA (ceRNA) network mechanism. At present, the studies of the circRNA profiles and circRNA-associated ceRNA networks in the IgAN are still scarce. This study aimed to elucidate the potential roles of circRNA-associated ceRNA networks of peripheral blood mononuclear cells (PBMCs) in IgAN patients Method CircRNA sequencing was used to identify the differential expressed circRNAs (DEcircRNAs) of PBMCs in IgAN and healthy controls; limma packages from data sets GSE25590 and GSE73953 in the Gene Expression Omnibus (GEO) database, were used to identify differentially expressed micro RNAs (miRNAs) and message RNAs (mRNAs). A circRNA-miRNA-mRNA ceRNA network was constructed to further investigate the mechanisms of IgAN. Then, GO analysis and KEGG enrichment analyses were used to annotate the genes involved in the circRNA-associated ceRNA network. Further, Protein-protein interaction (PPI) networks were established to screen potential hub genes, by using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Last, a quantitative real-time polymerase chain reaction (qRT-PCR) was applied to verify the hub genes in the ceRNA network. Result A total of 145 circRNAs, 22 miRNAs, and 1,117 mRNAs were differentially expressed in IgAN compared with controls (P < 0.05). A ceRNA network was constructed which contained 16 DEcircRNAs, 72 differential expressed mRNAs (DEmRNAs) and 11 differential expressed miRNAs (DEmiRNAs). KEGG pathway enrichment analysis illustrated the underlying biological functions of the ceRNA-associated genes, such as Nitrogen compound metabolic process, COPII-coated ER to Golgi transport vesicle, CAMP response element protein binding process (P < 0.01); meanwhile, Hepatitis B, GnRH signaling, and Prion disease were the most significant enrichment GO terms (P < 0.01). PPI network based on STRING analysis identified 4 potentially hub genes. Finally, Ankyrin repeat and SOCS box containing 16 (ASB16), SEC24 homolog C, COPII coat complex component (SEC24C) were confirmed by qRT-PCR (P < 0.05) and were identified as the hub genes of the ceRNA network in our study. Conclusion Our study identified a novel circRNA-mediated ceRNA regulatory network mechanisms in the pathogenesis of IgAN.

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Long non-coding RNA expression profiling in the lungs of pulmonary arterial hypertension rats with acute inflammation

Pulmonary Circulation ◽

10.1177/2045894019879393 ◽

2019 ◽

Vol 9 (4) ◽

pp. 204589401987939

Author(s):

Yue Yang ◽

Yanan Cao ◽

Gang Qin ◽

Lu Wang ◽

Qian Li ◽

...

Keyword(s):

Pulmonary Arterial Hypertension ◽

Arterial Hypertension ◽

Acute Inflammation ◽

Expression Profiles ◽

Differentially Expressed ◽

Control Group ◽

Messenger Rnas ◽

Bioinformatics Analyses ◽

Qrt Pcr ◽

Pulmonary Arterial

Background We performed RNA-sequencing to investigate the changes and expression profiles in long non-coding RNAs (lncRNAs) and their potential functional roles in the lungs of pulmonary arterial hypertension rats responding to acute inflammation. Methods To establish a pulmonary arterial hypertension rat model, monocrotaline was injected intraperitoneally and lipopolysaccharide was given to induce acute inflammation. Selected lncRNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR). Bioinformatics analyses were carried out to predict the potential biological roles of key lncRNAs. Results Twenty-eight lncRNAs and seven mRNAs with elevated expression and 202 lncRNAs and 36 mRNAs with decreased expression were found in the lung tissues of lipopolysaccharide-treated pulmonary arterial hypertension rats compared with control group. The qRT-PCR validation results were consistent with the bioinformatics analysis. Gene ontology analyses showed that the mRNAs and lncRNAs were differentially expressed in different pathways regarding biological process, cellular components, and molecular function. The functions of differentially expressed messenger RNAs (DEmRNAs) and DElncRNAs were indicated by Kyoto Encyclopedia of Genes and Genomes enrichment. Conclusion The DEmRNAs co-expressed with DElncRNAs were obviously enriched in inflammation. DElncRNAs and DEmRNAs in the lungs of pulmonary arterial hypertension rats changed with acute inflammation may provide new insights into the pathogenesis of pulmonary arterial hypertension.

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Predicting Hub Genes of Glioblastomas Based on Support Vector Machine Combined with CFS algorithms

Current Bioinformatics ◽

10.2174/1574893615999200819162140 ◽

2020 ◽

Vol 15 ◽

Author(s):

Chun Qiu ◽

Sai Li ◽

Shenghui Yang ◽

Lin Wang ◽

Aihui Zeng ◽

...

Keyword(s):

Support Vector Machine ◽

Expression Profiles ◽

Independent Set ◽

Classification Model ◽

Support Vector ◽

Feature Subset ◽

Hub Genes ◽

Effective Prevention ◽

Key Genes ◽

Control Samples

Aim: To search the genes related to the mechanisms of the occurrence of glioma and to try to build a prediction model for glioblastomas. Background: The morbidity and mortality of glioblastomas are very high, which seriously endangers human health. At present, the goals of many investigations on gliomas are mainly to understand the cause and mechanism of these tumors at the molecular level and to explore clinical diagnosis and treatment methods. However, there is no effective early diagnosis method for this disease, and there are no effective prevention, diagnosis or treatment measures. Methods: First, the gene expression profiles derived from GEO were downloaded. Then, differentially expressed genes (DEGs) in the disease samples and the control samples were identified. After that, GO and KEGG enrichment analyses of DEGs were performed by DAVID. Furthermore, the correlation-based feature subset (CFS) method was applied to the selection of key DEGs. In addition, the classification model between the glioblastoma samples and the controls was built by an Support Vector Machine (SVM) based on selected key genes. Results and Discussion: Thirty-six DEGs, including 17 upregulated and 19 downregulated genes, were selected as the feature genes to build the classification model between the glioma samples and the control samples by the CFS method. The accuracy of the classification model by using a 10-fold cross-validation test and independent set test was 76.25% and 70.3%, respectively. In addition, PPP2R2B and CYBB can also be found in the top 5 hub genes screened by the protein– protein interaction (PPI) network. Conclusions: This study indicated that the CFS method is a useful tool to identify key genes in glioblastomas. In addition, we also predicted that genes such as PPP2R2B and CYBB might be potential biomarkers for the diagnosis of glioblastomas.

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Genome-Wide Analysis of mRNA and Long Noncoding RNA Profiles in Chronic Actinic Dermatitis

BioMed Research International ◽

10.1155/2017/7479523 ◽

2017 ◽

Vol 2017 ◽

pp. 1-15 ◽

Cited By ~ 2

Author(s):

Dongyun Lei ◽

Lechun Lv ◽

Li Yang ◽

Wenjuan Wu ◽

Yong Liu ◽

...

Keyword(s):

Noncoding Rna ◽

Differentially Expressed ◽

Pathogenetic Mechanism ◽

Bioinformatics Analyses ◽

Inflammatory Lesions ◽

Qrt Pcr ◽

Exposed Skin ◽

Genome Wide ◽

Chronic Actinic Dermatitis ◽

Solid Foundation

Chronic actinic dermatitis (CAD), a photosensitive dermatosis, is characterized by inflammatory lesions, especially on sun-exposed skin. However, its pathogenesis remains unclear. In this study, second-generation RNA sequencing and comprehensive bioinformatics analyses of mRNAs and long noncoding RNAs (lncRNAs) were performed to determine the transcriptome profiles of patients with CAD. A total 6889 annotated lncRNAs, 341 novel lncRNAs, and 65091 mRNAs were identified. Interestingly, patients with CAD and healthy controls showed distinct transcriptome profiles. Indeed, 198 annotated (81.48%) and 45 novel (18.52%) lncRNAs were differentially expressed between the two groups. GO, KEGG, and RGSEA analyses of lncRNAs showed that inflammatory and immune response related pathways played crucial roles in the pathogenetic mechanism of CAD. In addition, we unveiled key differentially expressed lncRNAs, including lncRNA RP11-356I2.4 which plays a role probably by regulating TNFAIP3 and inflammation. qRT-PCR data validated the differentially expressed genes. The newly identified lncRNAs may have potential roles in the development of CAD; these findings lay a solid foundation for subsequent functional exploration of lncRNAs and mRNAs as therapeutic targets for CAD.

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Identification of differentially expressed microRNAs in outgrowth embryos compared with blastocysts and non-outgrowth embryos in mice

Reproduction Fertility and Development ◽

10.1071/rd18161 ◽

2019 ◽

Vol 31 (4) ◽

pp. 645 ◽

Cited By ~ 6

Author(s):

Jihyun Kim ◽

Jaewang Lee ◽

Jin Hyun Jun

Keyword(s):

Bioinformatics Analysis ◽

Preimplantation Embryo ◽

Expression Profiles ◽

In Silico Analysis ◽

Differentially Expressed ◽

Recurrent Implantation Failure ◽

Preimplantation Embryo Development ◽

Mirna Expression Profiles ◽

Differentially Expressed Mirnas ◽

Silico Analysis

Recurrent implantation failure (RIF) is one of the main causes for the repeated failure of IVF, and the major reason for RIF is thought to be a miscommunication between the embryo and uterus. However, the exact mechanism underlying embryo–uterus cross-talk is not fully understood. The aim of the present study was to identify differentially expressed microRNAs (miRNAs) among blastocysts, non-outgrowth and outgrowth embryos in mice using microarray analysis. A bioinformatics analysis was performed to predict the potential mechanisms of implantation. The miRNA expression profiles differed significantly between non-outgrowth and outgrowth embryos. In all, 3163 miRNAs were detected in blastocysts and outgrowth embryos. Of these, 10 miRNA candidates (let-7b, miR-23a, miR-27a, miR-92a, miR-183, miR-200c, miR-291a, miR-425, miR-429 and miR-652) were identified as significant differentially expressed miRNAs of outgrowth embryos by in silico analysis. The expression of the miRNA candidates was markedly changed during preimplantation embryo development. In particular, let-7b-5p, miR-200c-3p and miR-23a-3p were significantly upregulated in outgrowth embryos compared with non-outgrowth blastocysts. Overall, differentially expressed miRNAs in outgrowth embryos compared with blastocysts and non-outgrowth embryos could be involved in embryo attachment, and interaction between the embryo proper and maternal endometrium during the implantation process.

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